Job-related conversations across India today talk heavily about white and blue-collar jobs. However, most of the jobs that continue to build India up today don’t really fit neatly into one of these two boxes.
In India, where industries like manufacturing, infrastructure, logistics, utilities, and services continue to rise, it’s grey-collar talent that is now in demand and for good reason. Grey-collar jobs lie between rigid definitions of white- and blue-collar jobs, requiring both skill and physical activity.
Like most jobs today, grey-collar roles have also been significantly impacted by evolving technologies such as AI and IoT. However, due to the high-risk nature of various grey-collar roles, combined with their unique blend of brain and brawn, the changes brought on by new technologies create both advantages and challenges.
What Do We Mean by “Grey-Collar” Work?
Most white-collar jobs focus on formal skill training and are conducted in a sit-down/office environment. In contrast, blue-collar roles primarily involve manual/physical labour with a focus on hands-on execution in physically demanding industries.
Grey-collar work utilises both the physical activity often associated with blue-collar jobs and also demands formal skill training, which is primarily required in white-collar jobs. Fittingly, grey-collar jobs span the spectrum between physical and mental work, serving as an umbrella for a diverse set of roles.
In grey-collar work, physical execution is combined with judgment, coordination, and accountability, showcasing the practical nature of today’s world. Though the term may be new to some, the jobs that it represents have existed for a long time and will likely continue to grow.
Grey-Collar Jobs You Might Know Well
If you take a quick look around you, you will find yourself surrounded by those in grey-collar roles. These are people who have played critical roles in your life since a young age and will continue to do so in the future.
Some of the more common grey-collar roles include:
Airline Pilots and flight attendants
Example Certification: Commercial Pilot Licence (CPL), Diploma in Air Hostess
Both pilots and flight attendants undergo rigorous training to ensure passenger safety and comfort. They do so by applying the knowledge in the real world. From how a plane lands to how medical aid is provided thousands of feet in the air, they learn it and then execute it regularly.
Chefs and hospitality professionals
Example Certification: IFCA Certified Master Chef (CMC), AHLEI Certified Hotel Administrator (CHA)
Your favourite restaurants often have chefs who went through years of culinary school and now stand on their feed everyday for hours to provide you with a mouthwatering experience. This is also applicable to the managers running hotels and restaurants who try to meet your needs to the best of their ability.
Hardware technicians
Example Certification: Diploma in Computer Hardware and Network Management, ESSCI Field Technician – Computing and Peripherals
Where there are machines, there must be those skilled in repairing and maintaining them. This line of work requires a thorough understanding of the machinery in question, whether it’s an everyday laptop or an industrial-scale wheat grinder.
Quality inspectors and safety officers
Example Certification: ISO 9001:2015 Lead Auditor, Advanced Diploma in Industrial Safety (ADIS)
Across industries, quality inspectors and safety officers require knowledge of legal and industrial norms, as well as an understanding of the products they inspect. In manufacturing and other physically intensive industries, inspection and preventive work also require active participation.
Field engineers
Example Certification: Bachelor’s degree in Engineering
Engineers, especially those involved in infrastructure development, must be both skilled and physically active. After all, building a dam requires a civil engineer’s knowledge and keen eyes.
Operations leads in warehouses, ports, and logistics hubs
Example Certification: ASCM Logistics, Transportation, and Distribution (CLTD), CILT Professional Certificate Program in Terminal Management
Even in locations with mostly blue-collar workers, management and leadership are often held by those with management qualifications or equivalent expertise. They remain involved in day-to-day physical operations while using their knowledge to make decisions.
Teachers and child care workers
Example Certification: Bachelor of Education, Diploma in Early Childhood Care and Education
Being a teacher and/or child care worker required through qualifications and knowledge. The real work involved everyday interactions with children, often standing on one’s feet all day and trying to keep up with active and curious children.
First responders
Example Certification: Registered Nurse (RN) Number, Police Basic Training Course, Basic Fireman Course
Policemen, nurses, and firemen all need thorough expertise and exemplary decision-making skills. With lives on the line, both their knowledge and their actions can have a huge impact on those in dire need of help.
Licensed/certified sales professionals
Example Certification: NISM Series V-A for Mutual Fund Distributors, RERA Registration Number
Many industries, including real estate, do not allow just anyone to conduct sales or even rental transactions. This ends up making realtors and other licensed/certified sales professionals a part of the grey-collar workforce.
Field Journalists
Example Certification: Post Graduate Diploma in Journalism (PGDJ)
In the field, journalists rely on their knowledge of the unfolding situation and current affairs, along with physical investigation of the case. As distributors of knowledge, their expertise is just as imperative as their investigation.
Why Expertise Matters in Grey-Collar Jobs
Expertise is essential to most grey-collar jobs, especially when it is formally recognised through certifications or other qualifications. The stakes in grey-collar jobs are often higher than in blue- or white-collar jobs, requiring thorough knowledge, sound judgment, and the ability to translate theory into practice.
- Scale and complexity of operations: Grey-collar workers in large plants and field teams are often responsible for the quality and safety of the work.
- Cost pressures + thin margins: In India, where most industries face high costs and thin profit margins, the expertise of grey-collar workers prevents costly errors.
- SOPs into decisions: The expertise of grey-collar workers regarding work makes them capable of making real-world decisions that balance physical capabilities with the need for efficiency.
The Convergence of Physical and Digital Work
As technology around the world evolves by leaps and bounds, the physical work of grey-collar workers has begun to converge with digital work. While automation, AI, and IoT are transforming what physical work means for grey-collar workers, knowledge of these technologies has also become imperative for them.
While technologies have automated certain physical and mental tasks, they have also created new tasks that keep grey-collar workers on their toes.
The latest advancements are not just changing the tools used within certain grey-collar jobs but also the very nature of their work. But does it reduce the need for expertise or physical presence?
Decidedly not.
Not unlike humans, machines are also prone to error. While they might make certain tasks easier and processes more efficient, the final judgment call and evaluation of the work continues to rely on humans.
The Role of IoT in Grey-Collar Work
The Internet of Things (IoT) heralded the era of everyday automation. Since then, gadgets built for easy data communication have become almost an inescapable part of everyday life. In many ways, they have improved the quality of life for many, and their usage has also transformed certain aspects of grey-collar jobs.
Consider the medical field, where the use of portable sensors has made it easier to collect crucial metrics. Keeping track of heart rate for at-risk patients can provide medical professionals with crucial data that would have previously required long hospital observation stays.
For chefs, there are smart fridges, temperature sensors, and smart ovens. Field engineers have begun using sensors to monitor various material quality and environmental factors. Even teachers are now using smart boards that provide the convenience of blackboards with the options of a computer.
The use of IoT has helped many grey-collar workers shift from a reactive firefighting strategy to a predictive maintenance mentality, especially when it comes to tracking metrics. In other words, IoT has opened up a world of possibilities for most grey-collar workers while increasing convenience for all.
How AI Is Being Embedded into Grey-Collar Roles
Where IoT has made grey-collar work more convenient, Artificial Intelligence (AI) has made it much smarter and faster. The very metrics that IoT provides can be used by AI to predict possible situations.
The predictive and analytical abilities of AI have significantly reduced the repetitive aspects of grey-collar jobs while also providing more structure in certain areas. The added intelligence from AI serves as a supporting and verifying tool that helps boost the speed and efficiency of certain tasks.
Despite its capabilities, AI remains a support layer and not a decision-maker in most grey-collar areas. A large part of it stems from the need for human intervention to recheck calculations and suggestions through an expert lens, taking into account factors the AI might have missed.
While AI does help reduce the cognitive load on many grey-collar workers, the tasks still require human accountability, which makes grey-collar roles so unique. For example, no matter the designs and changes suggested by an AI, how a dam should really be built is still upto the field engineer, who will have to put both his skills and reputation on the line when incorporating any suggestions from the AI.
From Execution to Judgment: How Grey-Collar Work Is Evolving
With the inclusion of AI and IoT, most grey-collar jobs have seen a reduction in repetitive tasks. IoT-based devices, in particular, have helped many grey-collar workers better understand their work-related metrics while reducing the effort required to measure them.
However, as the availability of metrics and possible work options has increased, so has the need for situational awareness and prioritisation. This means that the human ability o asses a situation and make a clear judgment has become more important than ever.
With a large set of data and options at hand, grey-collar workers have increasingly relied on their expertise and experience to make the right decisions. The modern technology, while extremely advanced, is still not making the final shots.
As such, it falls on grey-collar workers not only to act as the final authority in high-risk environments, but also to keep up with all the new knowledge available to them.
New Skill Expectations for Grey-Collar Workers
That technologies like AI are being integrated across industries is no news. It does, however, change the skill expectations employers have of their employees. Apart from expertise in their own area of work, many grey-collar workers now also have to upskill in digital knowledge.
This includes basics such as reading dashboards, understanding alerts, and monitoring trends. In more advanced setups, some grey-collar workers are now also expected to become fluent in AI and AI-enabled tools.
More importantly, grey-collar workers have to learn how the new technologies and tools translate into their line of work. It becomes much more than understanding the basics of AI and IoT. Rather, it’s the cross-functional understanding of the technology and the work itself that grey-collar workers must develop to keep up with the changing world.
How Manager Roles Are Changing
It is not just employees who have seen a shift in work expectations in grey-collar industries. While employees are learning new ways technology can assist them, managers and supervisors must understand how to align their human employees with the technological part of their workflow.
It is up to those in leadership not only to point out the advantages of metrics and the options provided by the new tools, but also to make them a priority. When managers emphasise translating data insights into daily priorities, employees follow suit by utilising those insights in their work.
Managers also keep a keen eye on how their employees use technology to improve their work. With the same tools available to all, it is how one uses them that sets them apart from the rest. In this, human creativity and ingenuity can exponentially boost what a tool is really capable of.
At the same time, managers must ensure that any AI recommendations are treated only as recommendations. Warn employees against blindly relying on AI and emphasise the importance of verifying not only AI outputs but also any metrics gathered with the latest tools.
Real Concerns on the Ground
Despite the promised advancements that come with IoT and AI, grey-collar work areas also face rising concerns about their increasing use across sectors. With most grey-collar jobs requiring human touch and judgement, these concerns raise serious questions that cannot be ignored.
Job insecurity and resistance to technology adoption
Like many white-collar and blue-collar industries, the rising use of AI has also generated the fear of job loss among grey-collar workers. While some fear that their job might be completely replaced by AI, others fear that they might not be able to keep up with evolving technologies, leaving them behind in the race to use certain tools effectively.
Risks of over-automation and skill erosion
With the rise in automation, there has always been a question of “how far is too far?” While automation can reduce a lot of physical and mental workload, it also raises the question of whether it may come at the cost of people losing the very skill that makes their job what it is.
Consider this: if a nurse always relies on a heart monitor to measure a patient’s heartbeat, will they still be able to measure the heartbeat in the absence of a machine? With automation reducing the need for certain tasks, there is fear that humans might not be able to perform them on their own if needed.
Digital access and language barriers
Even as the world builds itself around IoT and AI, in many areas across India, internet and digital access remain a hard challenge. This heavily hampers the output quality of certain grey-collar workers, not because of a lack of skill but because they are unable to access tools that address unique challenges in the area, including a language barrier between the user and the tool itself.
Safety, accountability, and ethical responsibility
One of the biggest concerns with AI-assisted decisions has been safety standards, accountability, and ethical responsibility. In grey-collar areas, where the physical stakes are much higher, and the risk to quality of life is so, an AI’s ideal solutions do not always translate.
The Upskilling Reality in India
Despite the heavy emphasis placed on the need for upskilling in grey-collar areas, certain ground realities make the task much harder than one might expect. The unique nature of grey-collar jobs often clashes with traditional setups of training methods, making the learning process that much harder.
- Classroom v/s Workspace: Training methods that are limited to online/offline classrooms often miss the mark on how a given piece of technology might work in real life. Even most simulations present an idealised scenario, missing the unexpected physical aspects of a grey-collar role.
- Learning constraints: Most grey-collar workers have non-traditional shifts, making it hard to stick to rigid learning schedules. Language diversity and varying education levels, especially in the digital space, can also serve as barriers to digital upskilling.
For most grey-collar areas, the best way to train is to combine theoretical scenarios with practical realities. Showcasing how modern tools work in real life, in the actual workplace, can help a grey-collar worker learn much faster.
Using microlearning, simulations, vernacular content, and on-the-job coaching can all help in boosting the digital knowledge of grey-collar workers, creating a smarter work pipeline that combines digital advancements with human judgment.
How Organisations Must Correct Course
When incorporating the latest technology into their work pipeline, organisations often make common mistakes that can cost them significantly down the line. This includes:
- Treating grey-collar workers as passive “users” of technology
- Implementing AI and IoT without redefining roles and decision rights
- Underinvesting in change management, communication, and supervisor enablement
For true incorporation of technology into grey-collar roles, human expertise should be treated as even more valuable rather than seen as replaceable. The goal of the technology should not be simply make the work faster but to make it better through the precision of machinery and the keenness of humans.
This requires creating “good” workflows that account for both the physical and mental aspects of a grey-collar role. Some simple but critical steps that companies can take to do so include:
- Co-creating digital solutions with technicians, supervisors, and field staff.
- Redesigning jobs, workflows, and accountability instead of just adding tools.
- Aligning AI and IoT investments with workforce strategy and skilling plans.
- Measuring success through safety, uptime, confidence, and quality and not just efficiency
While efficiency may seem like the ideal end goal, one cannot ignore factors such as compliance, workplace environment, and the quality of work. All of these metrics often rely on human oversight rather than mechanical work, making human presence in grey-collar areas more important than ever.
In the End…
Grey-collar workers have become key to India’s transformation on many fronts. As white-collar workers become less dependent on location, it’s grey-collar workers whose expertise is driving more employers to India.
The importance of developing expertise that includes both physical and mental labour, while incorporating the latest digital advancements, is becoming more imperative by the day and for good reasons.
What both organisations and workers need to focus on is moving from automation anxiety to capability building. Transformation, no matter the industry, is inevitable. As such, it becomes important to uphold the human necessity in any workflow, especially through upskilling and digital literacy.
Incorporating any technology should be weighed against whether it will redefine the work itself or simply digitise certain tasks. How each scenario will impact existing employees, the company’s standards, and its core values should be considered before any concrete decisions are made.
